Stability of motor output with variable network architectures

DESCRIPTION (provided by applicant): Plasticity is the mechanism for development and learning, as much as a cause of pathology. The neural circuits in the brain that are responsible for specific functions have to be both flexible to allow learning and adaptive behavior, and stable to ensure constant function and endurance of learned behaviors. In order to reconcile the need to change synaptic connections and intrinsic neuronal properties with the need to maintain long-term stability, regulatory mechanisms have to be employed that keep plastic changes within functional boundaries. This proposal focuses on how the nervous system can produce stable output activity, both over time, and across individuals. Homeostatic mechanisms that maintain stable neuronal activity over time are relatively well described at the level of single neurons and pairs of synaptic partners, but little is known about how this translates into the stable performance of and entire network of neurons. Network activity is relatively straightforward to monitor in small circuits that produce rhythmic motor behaviors, like the crustacean stomatogastric ganglion. Across individuals, the rhythmic patterns produced by these circuits are very consistent in the relative timing between different groups of neurons, even though the network architecture is variable, as some neuron types exist in different numbers of copies. The goal of the experiments proposed here is to identify which parameters of the synaptic interactions and intrinsic neuronal properties are regulated to compensate for the different network architectures. Individual neurons may adjust their firing patterns to achieve stable network performance. The strength of the synaptic connections onto postsynaptic partners, or the response properties of the postsynaptic neurons may be adjusted in a way that ensures similar total synaptic efficacy. This may also be reflected at the level of neuronal morphology and the abundance of synaptic contacts. Finally, it will be tested if experimental changes of the circuit architecture that result in acute changes of network activity can be compensated over time. It is of fundamental importance to understand the balance of homeostasis and plasticity in the brain, because this balance is lost in neurodegenerative diseases like Alzheimer's and epilepsy, with devastating consequences. In addition, unbalanced plasticity can hinder recovery from stroke or CNS injury.